Complex continuous optimization problems widely exist nowadays due to the fast
development of the economy and society. Moreover, the technologies like Internet of things …

Confronted with increasingly complex industrial scenarios, limited transportation resources
and complicated time constraints introduce significant challenges to production efficiency …

Job shop scheduling (JSS) is a process of optimizing the use of limited resources to improve
the production efficiency. JSS has a wide range of applications, such as order picking in the …

Dynamic flexible job shop scheduling (JSS) is an important combinatorial optimization
problem with complex routing and sequencing decisions under dynamic environments …

Recently, energy conservation in manufacturing industry, particular in energy-intensive
industries, receives much attention in order to meet the environmental protection and …

Inthis study, a flexible job shop scheduling problem with time-of-use electricity price
constraint is considered. The problem includes machine processing speed, setup time, idle …

Dynamic scheduling methods are essential and critical to manufacturing systems because of
uncertain events in the production process, such as new job insertions, order cancellations …

Against the background of smart manufacturing and Industry 4.0, how to achieve real-time
scheduling has become a problem to be solved. In this regard, automatic design for shop …

In the actual production, the insertion of new job and machine preventive maintenance (PM)
are very common phenomena. Under these situations, a flexible job-shop rescheduling …

Evolutionary multitask multiobjective learning has been widely used for handling more than
one multiobjective task simultaneously. However, it is rarely used in dynamic combinatorial …